DFdistr {shotGroups} | R Documentation |
Lookup table for distribution of range statistics and Rayleigh sigma
Description
Lookup table for the distribution of range statistics and Rayleigh sigma from a Monte Carlo simulation of circular bivariate normal shot groups with 0 mean and variance 1 in both directions. Includes the first four moments and several quantiles of the distribution of extreme spread, figure of merit, bounding box diagonal, and Rayleigh sigma for each combination of number of shots per group and number of groups, repeated 10 million times.
Usage
data(DFdistr)
Format
A data frame with 590 observations on the following 77 variables.
- n
number of shots in each group. One of 2, 3, ..., 49, 50, 45, ..., 95, 100.
- nGroups
number of groups with individual simulated range statistics that were averaged over to yield the final value. One of 1, 2, ..., 9, 10.
- nShots
total number of shots, i.e.,
n*nGroups
.- ES_M
Extreme spread mean over all Monte Carlo simulations
- ES_V
Extreme spread variance over all Monte Carlo simulations
- ES_SD
Extreme spread standard deviation over all Monte Carlo simulations
- ES_CV
Extreme spread coefficient of variation over all Monte Carlo simulations
- ESSQ_M
Squard extreme spread mean over all Monte Carlo simulations
- ESSQ_V
Squared extreme spread variance over all Monte Carlo simulations
- ES_SKEW
Extreme spread skewness over all Monte Carlo simulations (smoothed)
- ES_KURT
Extreme spread kurtosis over all Monte Carlo simulations (smoothed)
- ES_MED
Extreme spread median (50% quantile) over all Monte Carlo simulations
- ES_Q005
Extreme spread 0.5% quantile over all Monte Carlo simulations
- ES_Q025
Extreme spread 2.5% quantile over all Monte Carlo simulations
- ES_Q050
Extreme spread 5% quantile over all Monte Carlo simulations
- ES_Q100
Extreme spread 10% quantile over all Monte Carlo simulations
- ES_Q250
Extreme spread 25% quantile over all Monte Carlo simulations
- ES_Q500
Extreme spread 50% quantile (median) over all Monte Carlo simulations
- ES_Q750
Extreme spread 75% quantile over all Monte Carlo simulations
- ES_Q900
Extreme spread 90% quantile over all Monte Carlo simulations
- ES_Q950
Extreme spread 95% quantile over all Monte Carlo simulations
- ES_Q975
Extreme spread 97.5% quantile over all Monte Carlo simulations
- ES_Q995
Extreme spread 99.5% quantile over all Monte Carlo simulations
- FoM_M
Figure of merit mean over all Monte Carlo simulations
- FoM_V
Figure of merit variance over all Monte Carlo simulations
- FoM_SD
Figure of merit standard deviation over all Monte Carlo simulations
- FoM_CV
Figure of merit coefficient of variation over all Monte Carlo simulations
- FoM_SKEW
Figure of merit skewness over all Monte Carlo simulations (smoothed)
- FoM_KURT
Figure of merit kurtosis over all Monte Carlo simulations (smoothed)
- FoM_MED
Figure of merit median (50% quantile) over all Monte Carlo simulations
- FoM_Q005
Figure of merit 0.5% quantile over all Monte Carlo simulations
- FoM_Q025
Figure of merit 2.5% quantile over all Monte Carlo simulations
- FoM_Q050
Figure of merit 0.25% quantile over all Monte Carlo simulations
- FoM_Q100
Figure of merit 10% quantile over all Monte Carlo simulations
- FoM_Q250
Figure of merit 25% quantile over all Monte Carlo simulations
- FoM_Q500
Figure of merit 50% quantile (median) over all Monte Carlo simulations
- FoM_Q750
Figure of merit 75% quantile over all Monte Carlo simulations
- FoM_Q900
Figure of merit 90% quantile over all Monte Carlo simulations
- FoM_Q950
Figure of merit 95% quantile over all Monte Carlo simulations
- FoM_Q975
Figure of merit 97.5% quantile over all Monte Carlo simulations
- FoM_Q995
Figure of merit 99.5% quantile over all Monte Carlo simulations
- D_M
Bounding box diagonal mean over all Monte Carlo simulations
- D_V
Bounding box diagonal variance over all Monte Carlo simulations
- D_SD
Bounding box diagonal standard deviation over all Monte Carlo simulations
- D_CV
Bounding box diagonal coefficient of variation over all Monte Carlo simulations
- D_SKEW
Bounding box diagonal skewness over all Monte Carlo simulations (smoothed)
- D_KURT
Bounding box diagonal kurtosis over all Monte Carlo simulations (smoothed)
- D_MED
Bounding box diagonal median (50% quantile) over all Monte Carlo simulations
- D_Q005
Bounding box diagonal 0.5% quantile over all Monte Carlo simulations
- D_Q025
Bounding box diagonal 2.5% quantile over all Monte Carlo simulations
- D_Q050
Bounding box diagonal 5% quantile over all Monte Carlo simulations
- D_Q100
Bounding box diagonal 10% quantile over all Monte Carlo simulations
- D_Q250
Bounding box diagonal 25% quantile over all Monte Carlo simulations
- D_Q500
Bounding box diagonal 50% quantile (median) over all Monte Carlo simulations
- D_Q750
Bounding box diagonal 75% quantile over all Monte Carlo simulations
- D_Q900
Bounding box diagonal 90% quantile over all Monte Carlo simulations
- D_Q950
Bounding box diagonal 95% quantile over all Monte Carlo simulations
- D_Q975
Bounding box diagonal 97.5% quantile over all Monte Carlo simulations
- D_Q995
Bounding box diagonal 99.5% quantile over all Monte Carlo simulations
- RS_M
Rayleigh sigma mean over all Monte Carlo simulations
- RS_V
Rayleigh sigma variance over all Monte Carlo simulations
- RS_SD
Rayleigh sigma standard deviation over all Monte Carlo simulations
- RS_CV
Rayleigh sigma coefficient of variation over all Monte Carlo simulations
- RS_SKEW
Rayleigh sigma skewness over all Monte Carlo simulations (smoothed)
- RS_KURT
Rayleigh sigma kurtosis over all Monte Carlo simulations (smoothed)
- RS_MED
Rayleigh sigma median (50% quantile) over all Monte Carlo simulations
- RS_Q005
Rayleigh sigma 0.5% quantile over all Monte Carlo simulations
- RS_Q025
Rayleigh sigma 2.5% quantile over all Monte Carlo simulations
- RS_Q050
Rayleigh sigma 5% quantile over all Monte Carlo simulations
- RS_Q100
Rayleigh sigma 10% quantile over all Monte Carlo simulations
- RS_Q250
Rayleigh sigma 25% quantile over all Monte Carlo simulations
- RS_Q500
Rayleigh sigma 50% quantile (median) over all Monte Carlo simulations
- RS_Q750
Rayleigh sigma 75% quantile over all Monte Carlo simulations
- RS_Q900
Rayleigh sigma 90% quantile over all Monte Carlo simulations
- RS_Q950
Rayleigh sigma 95% quantile over all Monte Carlo simulations
- RS_Q975
Rayleigh sigma 97.5% quantile over all Monte Carlo simulations
- RS_Q995
Rayleigh sigma 99.5% quantile over all Monte Carlo simulations
Details
The Monte Carlo distribution used 10 million repetitions in each scenario. One scenario was a combination of the n
shots in each group, and the nGroups
groups over which individual range statistics were averaged. Values for n
were 2, 3, ..., 49, 50, 45, ..., 95, 100. Values for nGroups
were 1, 2, ... 9, 10.
Skewness and kurtosis were smoothed using separate linear spline fits for each number of groups except for kurtosis of Rayleigh sigma which was fitted using the density of the gamma distribution.
Used in range2sigma
to estimate Rayleigh parameter sigma from range statistics, and in efficiency
to estimate the number of groups and total shots required to estimate the confidence interval (CI) for Rayleigh sigma with a given coverage probability (CI level) and width.
See the following source for an independent simulation, and for the rationale behind using it to estimate Rayleigh sigma:
http://ballistipedia.com/index.php?title=Range_Statistics
An older eqivalent simulation with less repetitions was done by Taylor and Grubbs (1975).
References
Taylor, M. S., & Grubbs, F. E. (1975). Approximate Probability Distributions for the Extreme Spread (BRL-MR-2438). Aberdeen Proving Ground, MD: U.S. Ballistic Research Laboratory.
See Also
range2sigma
,
efficiency
,
getMaxPairDist
,
getBoundingBox
,
getRayParam
Examples
data(DFdistr)
str(DFdistr)